Driven Computer science graduate with expertise in data engineering, machine learning ops and cloud computing. Passionate about leveraging analytical horsepower and automation to enable data-driven decision making. Proven ability to unlock business value through well-architected analytics solutions. Currently working on building this page
- Programming & Scripting: Python, R, SQL, Scala, Bash
- ML Frameworks: Scikit-Learn, PyTorch, TensorFlow
- Data & Tools: • ETL, Databricks, Streamsets, Airflow
- Databases: MySQL, Postgres, SQL Server, MongoDB, DynamoDB, ArangoDB, Teradata
- Data warehouse: Snowflake, AWS Redshift
- Bigdata tools: Airflow, Apache Spark, Nifi, Confluent Kafka, Glue, EMR, Hadoop
- Cloud Platforms: AWS, Azure
- Tools: Docker, Spark, Kubernetes
- Streamsets White belt (Certified)
- AWS Solutions Architect - Associate (Certified)
- AWS Cloud Practitioner - Foundational (Certified)
- Data science Lab - World Quant university (Certified)
- Nvidia - Deep learning foundations (Certified)
- Snowflake - Data Warehouse (Certified)
- Databricks spark associate developer (Trained)
- SnowPro Data engineer (Trained)
- Evaluated deep learning models like MLP and Boosting algorithms to detect anomalies
- Achieved 98% precision score, outperforming baseline by 5%
- Created a GARCH time series model for predicting asset volatility, acquired stock data through an API,
- Cleaned and stored it in an SQLite database, and built my own API to serve model predictions.
- Architected cloud ETL process loading 300+ GB/day into DynamoDB
- Enhanced reliability through validation rules in Python
- Created customer 360 model improving PEP identification accuracy by 15%
- Operationalized training through MLOps monitoring
- 📫 Reach me at krisrcb.dev@gmail.com